Machine learning researcher turned AI engineer. I build compact neural representations that keep local and temporal structure (satellite-image retrieval, 2-bit LLM inference) and I am now shipping that work as production-style AI services: RAG and agent pipelines, model serving, and drift-aware retraining.
Research
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Now (SKALA, Jul – Dec 2026)
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Encodes a full satellite image sequence once, keeps a compact patch grid, and reuses arbitrary subsets for regional queries without crop-and-re-encode overhead.
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Post-training quantization on a Factored E8 lattice: a 4 KB codebook that stays in GPU L1 cache, Sinkhorn-based weight scale normalization, and per-matrix adaptive critical-weight preservation with zero bit overhead. FE8 quantizes up to 6.8x faster than QTIP and decodes faster than FP16 on Llama-2-7B and Llama-3-8B.
kmudmlab/eptq · DOI 10.1145/3799682.3841056 |
| Project | What it demonstrates | Stack |
|---|---|---|
| EventHub SKALA team | Event-platform MSA with five services and Kafka; personalized recommendation that stacks collaborative-filtering KNN with an MLP to cover cold start (Hit@10 0.396 → 0.600) | Java, Spring Boot, JPA, Kafka, MariaDB, Python |
| KV-cache optimization review agent SKALA team | LangGraph pipeline of 10 agents that evaluates KV-cache optimization techniques from four perspectives; three RAG agents benchmarked across chunking, embeddings (bge-m3, e5, Qwen3-Embedding), and query rewriting | Python, LangGraph, LangChain, Vector DB, RAGAS |
| TSA checkpoint forecasting SKALA mini | FastAPI serving with an MLflow deployment gate, RMSE drift detection, warm-start retraining, and rule-based safe mode; cut service RMSE by 72.7% versus a static model during the COVID-19 collapse | Python, FastAPI, MLflow, LSTM, gradient boosting, Docker |
| Zhang et al. SKALA solo | Research-topic reader that finds overlapping prior work by embedding search over 10,326 papers; requirements, UI flow, OpenAPI, and ERD design | Service design, OpenAPI, DBML |
| KBO Schedule API | Automated collection and delivery of structured game schedules through a weekly GitHub Actions workflow and GitHub Pages | Python, JSON, GitHub Actions |
| Front-end Systems Lab | Responsive vanilla web portal with modular weather API integration and progressive HTML/CSS/JavaScript exercises | HTML, CSS, JavaScript, Open-Meteo |
| Network security monitoring | Four-person project combining graph-based features with deep learning for packet security monitoring | Python, PyTorch, PageRank, RWR |
Research
LLM & Agents
Engineering
| Period | Organization | Role |
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| Jul 2026 – Dec 2026 | SKALA 4th cohort | Full-stack AI service training: Python, Java/Spring Boot, Vue.js, Docker, Kubernetes, MSA, LangChain/LangGraph, RAG, agents, MLflow-based serving and AIOps |
| Aug 2023 – Feb 2026 | Data Mining Lab, Kookmin University | Undergraduate researcher, then M.S. researcher; satellite-image retrieval and LLM quantization |
| Mar 2024 – Feb 2026 | Kookmin University | M.S. in Computer Science · GPA 4.39/4.50 |
| Mar 2016 – Feb 2024 | Kookmin University | B.A. in Political Science & Diplomacy and B.S. in Computer Science (double major) |
Languages & credentials · OPIc IH (May 2026) · TOEIC 915 (Nov 2023)
Researching efficient representations from Seoul, South Korea.